Douglas Eck

According to our database, Douglas Eck authored at least 74 papers between 1999 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis.

Izzeddin Gur, Hiroki Furuta, Austin V. Huang, Mustafa Safdari, Yutaka Matsuo, Douglas Eck, Aleksandra Faust

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

PaLM: Scaling Language Modeling with Pathways.

Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, Parker Schuh, Kensen Shi, Sasha Tsvyashchenko, Joshua Maynez, Abhishek Rao, Parker Barnes, Yi Tay, Noam Shazeer, Vinodkumar Prabhakaran, Emily Reif, Nan Du, Ben Hutchinson, Reiner Pope, James Bradbury, Jacob Austin, Michael Isard, Guy Gur-Ari, Pengcheng Yin, Toju Duke, Anselm Levskaya, Sanjay Ghemawat, Sunipa Dev, Henryk Michalewski, Xavier Garcia, Vedant Misra, Kevin Robinson, Liam Fedus, Denny Zhou, Daphne Ippolito, David Luan, Hyeontaek Lim, Barret Zoph, Alexander Spiridonov, Ryan Sepassi, David Dohan, Shivani Agrawal, Mark Omernick, Andrew M. Dai, Thanumalayan Sankaranarayana Pillai, Marie Pellat, Aitor Lewkowycz, Erica Moreira, Rewon Child, Oleksandr Polozov, Katherine Lee, Zongwei Zhou, Xuezhi Wang, Brennan Saeta, Mark Diaz, Orhan Firat, Michele Catasta, Jason Wei, Kathy Meier-Hellstern, Douglas Eck, Jeff Dean, Slav Petrov, Noah Fiedel

J. Mach. Learn. Res., 2023

2022

Deduplicating Training Data Makes Language Models Better.

Katherine Lee, Daphne Ippolito, Andrew Nystrom, Chiyuan Zhang, Douglas Eck, Chris Callison-Burch, Nicholas Carlini

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021

Joint Attention for Multi-Agent Coordination and Social Learning.

Dennis Lee, Natasha Jaques, J. Chase Kew, Douglas Eck, Dale Schuurmans, Aleksandra Faust

CoRR, 2021

Emergent Social Learning via Multi-agent Reinforcement Learning.

Kamal Ndousse, Douglas Eck, Sergey Levine, Natasha Jaques

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

This time with feeling: learning expressive musical performance.

Sageev Oore, Ian Simon, Sander Dieleman, Douglas Eck, Karen Simonyan

Neural Comput. Appl., 2020

Multi-agent Social Reinforcement Learning Improves Generalization.

Kamal Ndousse, Douglas Eck, Sergey Levine, Natasha Jaques

CoRR, 2020

Toward Better Storylines with Sentence-Level Language Models.

Daphne Ippolito, David Grangier, Douglas Eck, Chris Callison-Burch

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Automatic Detection of Generated Text is Easiest when Humans are Fooled.

Daphne Ippolito, Daniel Duckworth, Chris Callison-Burch, Douglas Eck

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

Human and Automatic Detection of Generated Text.

Daphne Ippolito, Daniel Duckworth, Chris Callison-Burch, Douglas Eck

CoRR, 2019

Learning to Groove with Inverse Sequence Transformations.

Jon Gillick, Adam Roberts, Jesse H. Engel, Douglas Eck, David Bamman

Proceedings of the 36th International Conference on Machine Learning, 2019

A Learned Representation for Scalable Vector Graphics.

Raphael Gontijo Lopes, David Ha, Douglas Eck, Jonathon Shlens

Proceedings of the Deep Generative Models for Highly Structured Data, 2019

Music Transformer: Generating Music with Long-Term Structure.

Cheng-Zhi Anna Huang, Ashish Vaswani, Jakob Uszkoreit, Ian Simon, Curtis Hawthorne, Noam Shazeer, Andrew M. Dai, Matthew D. Hoffman, Monica Dinculescu, Douglas Eck

Proceedings of the 7th International Conference on Learning Representations, 2019

Enabling Factorized Piano Music Modeling and Generation with the MAESTRO Dataset.

Curtis Hawthorne, Andriy Stasyuk, Adam Roberts, Ian Simon, Cheng-Zhi Anna Huang, Sander Dieleman, Erich Elsen, Jesse H. Engel, Douglas Eck

Proceedings of the 7th International Conference on Learning Representations, 2019

Identifying the Intersections: User Experience + Research Scientist Collaboration in a Generative Machine Learning Interface.

Claire Kayacik, Sherol Chen, Signe Noerly, Jess Holbrook, Adam Roberts, Douglas Eck

Proceedings of the Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems, 2019

2018

An Improved Relative Self-Attention Mechanism for Transformer with Application to Music Generation.

Cheng-Zhi Anna Huang, Ashish Vaswani, Jakob Uszkoreit, Noam Shazeer, Curtis Hawthorne, Andrew M. Dai, Matthew D. Hoffman, Douglas Eck

CoRR, 2018

Learning a Latent Space of Multitrack Measures.

Ian Simon, Adam Roberts, Colin Raffel, Jesse H. Engel, Curtis Hawthorne, Douglas Eck

CoRR, 2018

Learning Latent Representations of Music to Generate Interactive Musical Palettes.

Adam Roberts, Jesse H. Engel, Sageev Oore, Douglas Eck

Proceedings of the Joint Proceedings of the ACM IUI 2018 Workshops co-located with the 23rd ACM Conference on Intelligent User Interfaces (ACM IUI 2018), 2018

Onsets and Frames: Dual-Objective Piano Transcription.

Curtis Hawthorne, Erich Elsen, Jialin Song, Adam Roberts, Ian Simon, Colin Raffel, Jesse H. Engel, Sageev Oore, Douglas Eck

Proceedings of the 19th International Society for Music Information Retrieval Conference, 2018

Learning via Social Awareness: Improving a Deep Generative Sketching Model with Facial Feedback.

Natasha Jaques, Jennifer McCleary, Jesse H. Engel, David Ha, Fred Bertsch, Douglas Eck, Rosalind W. Picard

Proceedings of the Workshop on Artificial Intelligence in Affective Computing, 2018

A Hierarchical Latent Vector Model for Learning Long-Term Structure in Music.

Adam Roberts, Jesse H. Engel, Colin Raffel, Curtis Hawthorne, Douglas Eck

Proceedings of the 35th International Conference on Machine Learning, 2018

Learning via social awareness: improving sketch representations with facial feedback.

Natasha Jaques, Jesse H. Engel, David Ha, Fred Bertsch, Rosalind W. Picard, Douglas Eck

Proceedings of the 6th International Conference on Learning Representations, 2018

Towards Mixed-initiative generation of multi-channel sequential structure.

Cheng-Zhi Anna Huang, Sherol Chen, Mark J. Nelson, Douglas Eck

Proceedings of the 6th International Conference on Learning Representations, 2018

A Neural Representation of Sketch Drawings.

David Ha, Douglas Eck

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Improving image generative models with human interactions.

Andrew Kyle Lampinen, David So, Douglas Eck, Fred Bertsch

CoRR, 2017

Learning and Evaluating Musical Features with Deep Autoencoders.

Mason Bretan, Sageev Oore, Douglas Eck, Larry P. Heck

CoRR, 2017

Counterpoint by Convolution.

Cheng-Zhi Anna Huang, Tim Cooijmans, Adam Roberts, Aaron C. Courville, Douglas Eck

Proceedings of the 18th International Society for Music Information Retrieval Conference, 2017

Online and Linear-Time Attention by Enforcing Monotonic Alignments.

Colin Raffel, Minh-Thang Luong, Peter J. Liu, Ron J. Weiss, Douglas Eck

Proceedings of the 34th International Conference on Machine Learning, 2017

Sequence Tutor: Conservative Fine-Tuning of Sequence Generation Models with KL-control.

Natasha Jaques, Shixiang Gu, Dzmitry Bahdanau, José Miguel Hernández-Lobato, Richard E. Turner, Douglas Eck

Proceedings of the 34th International Conference on Machine Learning, 2017

Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders.

Jesse H. Engel, Cinjon Resnick, Adam Roberts, Sander Dieleman, Mohammad Norouzi, Douglas Eck, Karen Simonyan

Proceedings of the 34th International Conference on Machine Learning, 2017

Tuning Recurrent Neural Networks with Reinforcement Learning.

Natasha Jaques, Shixiang Gu, Richard E. Turner, Douglas Eck

Proceedings of the 5th International Conference on Learning Representations, 2017

Deep Music: Towards Musical Dialogue.

Mason Bretan, Sageev Oore, Jesse H. Engel, Douglas Eck, Larry P. Heck

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2012

Machine Learning Methods for Music Discovery and Recommendation.

Douglas Eck

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

Building Musically-relevant Audio Features through Multiple Timescale Representations.

Philippe Hamel, Yoshua Bengio, Douglas Eck

Proceedings of the 13th International Society for Music Information Retrieval Conference, 2012

2011

Contextual tag inference.

Michael I. Mandel, Razvan Pascanu, Douglas Eck, Yoshua Bengio, Luca Maria Aiello, Rossano Schifanella, Filippo Menczer

ACM Trans. Multim. Comput. Commun. Appl., 2011

The need for music information retrieval with user-centered and multimodal strategies.

Cynthia C. S. Liem, Meinard Müller, Douglas Eck, George Tzanetakis, Alan Hanjalic

Proceedings of the 1st international ACM workshop on Music information retrieval with user-centered and multimodal strategies, Scottsdale, AZ, USA, November 28, 2011

1st international ACM workshop on music information retrieval with user-centered and multimodal strategies (MIRUM).

Cynthia C. S. Liem, Meinard Müller, Douglas Eck, George Tzanetakis

Proceedings of the 19th International Conference on Multimedia 2011, Scottsdale, AZ, USA, November 28, 2011

Temporal Pooling and Multiscale Learning for Automatic Annotation and Ranking of Music Audio.

Philippe Hamel, Simon Lemieux, Yoshua Bengio, Douglas Eck

Proceedings of the 12th International Society for Music Information Retrieval Conference, 2011

2010

Learning Tags that Vary Within a Song.

Michael I. Mandel, Douglas Eck, Yoshua Bengio

Proceedings of the 11th International Society for Music Information Retrieval Conference, 2010

Learning Features from Music Audio with Deep Belief Networks.

Philippe Hamel, Douglas Eck

Proceedings of the 11th International Society for Music Information Retrieval Conference, 2010

Scalable Genre and Tag Prediction with Spectral Covariance.

James Bergstra, Michael I. Mandel, Douglas Eck

Proceedings of the 11th International Society for Music Information Retrieval Conference, 2010

2009

Probabilistic models for melodic prediction.

Jean-François Paiement, Samy Bengio, Douglas Eck

Artif. Intell., 2009

Towards a musical beat emphasis function.

Matthew E. P. Davies, Mark D. Plumbley, Douglas Eck

Proceedings of the IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 2009

An Infinite Factor Model Hierarchy Via a Noisy-Or Mechanism.

Aaron C. Courville, Douglas Eck, Yoshua Bengio

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Steerable Playlist Generation by Learning Song Similarity from Radio Station Playlists.

François Maillet, Douglas Eck, Guillaume Desjardins, Paul Lamere

Proceedings of the 10th International Society for Music Information Retrieval Conference, 2009

Automatic Identification of Instrument Classes in Polyphonic and Poly-Instrument Audio.

Philippe Hamel, Sean Wood, Douglas Eck

Proceedings of the 10th International Society for Music Information Retrieval Conference, 2009

Workshop summary: Sparse methods for music audio.

Douglas Eck, Dan Ellis, Philippe Hamel

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2008

On the Use of Sparce Time Relative Auditory Codes for Music.

Pierre-Antoine Manzagol, Thierry Bertin-Mahieux, Douglas Eck

Proceedings of the ISMIR 2008, 2008

A distance model for rhythms.

Jean-François Paiement, Yves Grandvalet, Samy Bengio, Douglas Eck

Proceedings of the Machine Learning, 2008

2007

A Supervised Classification Algorithm for Note Onset Detection.

Alexandre Lacoste, Douglas Eck

EURASIP J. Adv. Signal Process., 2007

Automatic Generation of Social Tags for Music Recommendation.

Douglas Eck, Paul Lamere, Thierry Bertin-Mahieux, Stephen J. Green

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Using 3D Visualizations to Explore and Discover Music.

Paul Lamere, Douglas Eck

Proceedings of the 8th International Conference on Music Information Retrieval, 2007

Autotagging Music Using Supervised Machine Learning.

Douglas Eck, Thierry Bertin-Mahieux, Paul Lamere

Proceedings of the 8th International Conference on Music Information Retrieval, 2007

Beat Tracking using an Autocorrelation Phase Matrix.

Douglas Eck

Proceedings of the IEEE International Conference on Acoustics, 2007

2006

Aggregate features and ADABOOSTfor music classification.

James Bergstra, Norman Casagrande, Dumitru Erhan, Douglas Eck, Balázs Kégl

Mach. Learn., 2006

Can't Get You Out of My Head: A Connectionist Model of Cyclic Rehearsal.

Herbert Jaeger, Douglas Eck

Proceedings of the Modeling Communication with Robots and Virtual Humans, 2006

Predicting genre labels for artist using FreeDB.

James Bergstra, Alexandre Lacoste, Douglas Eck

Proceedings of the ISMIR 2006, 2006

Probabilistic Melodic Harmonization.

Jean-François Paiement, Douglas Eck, Samy Bengio

Proceedings of the Advances in Artificial Intelligence, 2006

2005

A Probabilistic Model for Chord Progressions.

Jean-François Paiement, Douglas Eck, Samy Bengio

Proceedings of the ISMIR 2005, 2005

Finding Meter in Music Using An Autocorrelation Phase Matrix and Shannon Entropy.

Douglas Eck, Norman Casagrande

Proceedings of the ISMIR 2005, 2005

Frame-Level Audio Feature Extraction Using AdaBoost.

Norman Casagrande, Douglas Eck, Balázs Kégl

Proceedings of the ISMIR 2005, 2005

A graphical model for chord progressions embedded in a psychoacoustic space.

Jean-François Paiement, Douglas Eck, Samy Bengio, David Barber

Proceedings of the Machine Learning, 2005

Geometry in sound: a speech/Music audio Classifier Inspired by an Image Classifier.

Norman Casagrande, Douglas Eck, Balázs Kégl

Proceedings of the 2005 International Computer Music Conference, 2005

2004

Biologically Plausible Speech Recognition with LSTM Neural Nets.

Alex Graves, Douglas Eck, Nicole Beringer, Jürgen Schmidhuber

Proceedings of the Biologically Inspired Approaches to Advanced Information Technology, 2004

2003

Kalman filters improve LSTM network performance in problems unsolvable by traditional recurrent nets.

Juan Antonio Pérez-Ortiz, Felix A. Gers, Douglas Eck, Jürgen Schmidhuber

Neural Networks, 2003

2002

Learning Nonregular Languages: A Comparison of Simple Recurrent Networks and LSTM.

Jürgen Schmidhuber, Felix A. Gers, Douglas Eck

Neural Comput., 2002

Finding temporal structure in music: blues improvisation with LSTM recurrent networks.

Douglas Eck, Jürgen Schmidhuber

Proceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing, 2002

Improving Long-Term Online Prediction with Decoupled Extended Kalman Filters.

Juan Antonio Pérez-Ortiz, Jürgen Schmidhuber, Felix A. Gers, Douglas Eck

Proceedings of the Artificial Neural Networks, 2002

Learning Context Sensitive Languages with LSTM Trained with Kalman Filters.

Felix A. Gers, Juan Antonio Pérez-Ortiz, Douglas Eck, Jürgen Schmidhuber

Proceedings of the Artificial Neural Networks, 2002

Learning the Long-Term Structure of the Blues.

Douglas Eck, Jürgen Schmidhuber

Proceedings of the Artificial Neural Networks, 2002

DEKF-LSTM.

Felix A. Gers, Juan Antonio Pérez-Ortiz, Douglas Eck, Jürgen Schmidhuber

Proceedings of the 10th Eurorean Symposium on Artificial Neural Networks, 2002

2001

Applying LSTM to Time Series Predictable Through Time-Window Approaches.

Felix A. Gers, Douglas Eck, Jürgen Schmidhuber

Proceedings of the 12th Italian Workshop on Neural Nets, 2001

A Network of Relaxation Oscillators that Finds Downbeats in Rhythms.

Douglas Eck

Proceedings of the Artificial Neural Networks, 2001

1999

Meter as Mechanism: A Neural Network Model that Learns Metrical Patterns.

Michael Gasser, Douglas Eck, Robert F. Port

Connect. Sci., 1999